Automatic learning of gait signatures for people identification

This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (i.e. optical flow components). We carry out a thorough experimental evaluation of the proposed CNN architecture on the challenging TUM-GAID dataset. The experimental results indicate that using spatio-temporal cuboids of optical flow as input data for CNN allows to obtain state-of-the-art results on the gait task with an image resolution eight times lower than the previously reported results (i.e. 80x60 pixels).Comment: Proof of concept paper. Technical report on the use of ConvNets (CNN) for gait recognition. Data and code: http://www.uco.es/~in1majim/research/cnngaitof.htm

B fields in OB stars (BOB): low-resolution FORS2 spectropolarimetry of the first sample of 50 massive stars

Within the context of the collaboration "B fields in OB stars (BOB)", we used the FORS2 low-resolution spectropolarimeter to search for a magnetic field in 50 massive stars, including two reference magnetic massive stars. Because of the many controversies of magnetic field detections obtained with the FORS instruments, we derived the magnetic field values with two completely independent reduction and analysis pipelines. We compare and discuss the results obtained from the two pipelines. We obtained a general good agreement, indicating that most of the discrepancies on magnetic field detections reported in the literature are caused by the interpretation of the significance of the results (i.e., 3-4 sigma detections considered as genuine, or not), instead of by significant differences in the derived magnetic field values. By combining our results with past FORS1 measurements of HD46328, we improve the estimate of the stellar rotation period, obtaining P = 2.17950+/-0.00009 days. For HD125823, our FORS2 measurements do not fit the available magnetic field model, based on magnetic field values obtained 30 years ago. We repeatedly detect a magnetic field for the O9.7V star HD54879, the HD164492C massive binary, and the He-rich star CPD -57 3509. We obtain a magnetic field detection rate of 6+/-4%, while by considering only the apparently slow rotators we derive a detection rate of 8+/-5%, both comparable with what was previously reported by other similar surveys. We are left with the intriguing result that, although the large majority of magnetic massive stars is rotating slowly, our detection rate is not a strong function of the stellar rotational velocity.Comment: 20 pages, 10 figures, 4 tables; accepted for publication on Astronomy & Astrophysic

Evaluation of CNN architectures for gait recognition based on optical flow maps

This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Sunflower yield: adjustement of data means by the combination of ANOVA and Regression models.

Sunflower is an important oilseed crop. Besides producing high quality edible oil for human consumption, it also produces meal for animal feeding, and is an alternative for biodiesel production as well. Sunflower is a crop well adapted to several environmental conditions and is tolerant to low temperatures and to relatively short periods of water stress. In Brazil, the sunflower cultivated area reaches 75,000 hectares and its yield averages 1,460 kg/ha (CONAB). Much effort has been spent on research work at management of sunflower and consequently higher yield. Research efforts are specifically directed to the control of diseases and pests, which can cause defoliation, damages to the roots, and yield losses. The need for macro- and micronutrient fertilizations is another research demanding aspect of the crop. Within this context, two extremely important aspects in solving these research demands are: the appropriate agronomical planning and the adequate experimental design. These procedures will allow decisions on selection of size and shape of plots, on experimental unit, on qualitative and quantitative factors, on experimental design, and on the choice of the variables that influence the response and the ways of choosing and distributing the treatments in the plots. The selection of the suitable statistical methods, which allow precise estimates of the treatments and the reduction of the residual variance, uncontrolled in the planning, is also essential. One of these methods is the Analysis of Covariance (ANCOVA). This method combines the Analysis of Variance (ANOVA) and the Regression Analysis, and besides controlling the experimental error, it adjusts the treatment means, thus helping the interpretation of the experimental results as well as the comparison of regressions among several groups of treatments. The model representing this combination is :Yij = ? + ? i + ? j + ? (xij - x.. ) +? ij , where: Yij is the observed value of the response variable; ? is the mean value of the response variable; i ? is the effect of treatment I, with i = 1, 2,?, I; j ? is the effect of the block j, with j = 1,2,?, J; ? is the effect of the combined linear regression Yij as related to x; ij x is the observed value of the co-variable; and ij ? is the experimental error associated toYij, with ?ij ?N (0,?2 ) . The covariate should not be influenced by the treatments initially tested, maintaining the independence among them. Therefore, the treatments were: one control (0), and the P2O5 dosages of 40 kg ha-1, 80 kg ha-1, 120 kg ha-1, and 160 kg ha-1, applied to the sunflower hybrid Aguara 4. The experiment was carried out as a randomized block design, with six replications and the variables studied were: yield (kg ha-1) and the number of achenes per sunflower plant. The descriptive analysis indicated consistency in the tests concerning normality and independence of errors, additivity of the model, and homogeneity of treatments variances. The F statistics presented significant response for the treatments, for the response variable and covariate (5.48 and 4.93), respectively. The highest sunflower yield, obtained with the dosage of 120 kg ha-1 P2O5, statistically differed only from the control (Tukey p? 0, 05). The ANCOVA, adjusted by the number of achenes, reduced the error variance from 49,768.84 to 32,887.40. An interesting fact is that after ANCOVA, the effect of treatments became non-significant (F = 2.62), even with the reduction of the error variance. The mean values adjusted by the Tukey-Kramer test were reduced when compared to the original means. The interaction of treatment with the covariable was not significant, indicating that the angular coefficients for the treatments were similar. We concluded that the analysis of covariance reduces the error variance and indicates the real significance of the treatment effects and of the angular coefficients for the non-homogeneous treatments

B fields in OB stars (BOB): Detection of a magnetic field in the He-strong star CPD-57{\deg} 3509

We report the detection of a magnetic field in the helium-strong star CPD-57 3509 (B2 IV), a member of the Galactic open cluster NGC3293, and characterise the star's atmospheric and fundamental parameters. Spectropolarimetric observations with FORS2 and HARPSpol are analysed using two independent approaches to quantify the magnetic field strength. A high-S/N FLAMES/GIRAFFE spectrum is analysed using a hybrid non-LTE model atmosphere technique. Comparison with stellar evolution models constrains the fundamental parameters of the star. We obtain a firm detection of a surface averaged longitudinal magnetic field with a maximum amplitude of about 1 kG. Assuming a dipolar configuration of the magnetic field, this implies a dipolar field strength larger than 3.3 kG. Moreover, the large amplitude and fast variation (within about 1 day) of the longitudinal magnetic field implies that CPD-57 3509 is spinning very fast despite its apparently slow projected rotational velocity. The star should be able to support a centrifugal magnetosphere, yet the spectrum shows no sign of magnetically confined material; in particular, emission in H{\alpha} is not observed. Apparently, the wind is either not strong enough for enough material to accumulate in the magnetosphere to become observable or, alternatively, some leakage process leads to loss of material from the magnetosphere. The quantitative spectroscopic analysis of the star yields an effective temperature and a logarithmic surface gravity of 23750+-250 K and 4.05+-0.10, respectively, and a surface helium fraction of 0.28+-0.02 by number. The surface abundances of C, N, O, Ne, S, and Ar are compatible with the cosmic abundance standard, whereas Mg, Al, Si, and Fe are depleted by about a factor of 2. This abundance pattern can be understood as the consequence of a fractionated stellar wind. CPD-57 3509 is one of the most evolved He-strong stars known.Comment: 15 pages, 11 figures. Accepted for publication in A&

Cell-based therapies for stroke : promising solution or dead end?

The introduction of recanalization procedures has revolutionized acute stroke management, although the narrow time window, strict eligibility criteria and logistical limitations still exclude the majority of patients from treatment. In addition, residual deficits are present in many patients who undergo therapy, preventing their return to premorbid status. Hence, there is a strong need for novel, and ideally complementary, approaches to stroke management. In preclinical experiments, cell-based treatments have demonstrated beneficial effects in the subacute and chronic stages following stroke [1; 2; 3] and therefore are considered a promising option to supplement current clinical practice. At the same time, great progress has been made in developing clinically feasible delivery and monitoring protocols [4]. However, efficacy results initially reported in clinical studies fell short of expectations [5] raising concerns that cell treatment might eventually share the ‘dead end fate’ of many previous experimental stroke therapies. This Research Topic reviews some of the latest and most innovative studies to summarize the state of the art in translational cell treatments for stroke

First report of Papaya ringspot virus-type W infecting fevillea species (cucurbitaceae) in South America.

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Effects due to a scalar coupling on the particle-antiparticle production in the Duffin-Kemmer-Petiau theory

The Duffin-Kemmer-Petiau formalism with vector and scalar potentials is used to point out a few misconceptions diffused in the literature. It is explicitly shown that the scalar coupling makes the DKP formalism not equivalent to the Klein-Gordon formalism or to the Proca formalism, and that the spin-1 sector of the DKP theory looks formally like the spin-0 sector. With proper boundary conditions, scattering of massive bosons in an arbitrary mixed vector-scalar square step potential is explored in a simple way and effects due to the scalar coupling on the particle-antiparticle production and localization of bosons are analyzed in some detail

Theoretical Aspects of the Fractional Quantum Hall Effect in Graphene

We review the theoretical basis and understanding of electronic interactions in graphene Landau levels, in the limit of strong correlations. This limit occurs when inter-Landau-level excitations may be omitted because they belong to a high-energy sector, whereas the low-energy excitations only involve the same level, such that the kinetic energy (of the Landau level) is an unimportant constant. Two prominent effects emerge in this limit of strong electronic correlations: generalised quantum Hall ferromagnetic states that profit from the approximate four-fold spin-valley degeneracy of graphene's Landau levels and the fractional quantum Hall effect. Here, we discuss these effects in the framework of an SU(4)-symmetric theory, in comparison with available experimental observations.Comment: 12 pages, 3 figures; review for the proceedings of the Nobel Symposium on Graphene and Quantum Matte